C-V2X technology-based road accident rescue method and system
阅读说明：本技术 一种基于c-v2x技术的道路事故救援方法及系统 (C-V2X technology-based road accident rescue method and system ) 是由 汤勇 苟尚进 于 2020-06-19 设计创作，主要内容包括：本发明属于智能驾驶技术领域,公开了一种基于C-V2X技术的道路事故救援方法及系统,基于C-V2X技术的道路事故救援系统包括碰撞检测模块、救援请求模块、故障检测模块、C-V2X控制模块、对公求救模块、对私求救模块、地图更新模块、定位模块、图像采集模块、图像分析模块、信号接收模块、路径规划模块、交流模块、通信模块；基于C-V2X技术的道路事故救援方法包括获取车辆信息,发出求救信号；进行地图更新对车辆位置的准确确定；得到事故车辆所在道路的道路拥挤度；进行救援路径规划。本发明基于C-V2X技术进行道路事故救援,具有准确性高、效率快的优势,能够实现对事故车辆或故障车辆的及时有效救援。(The invention belongs to the technical field of intelligent driving, and discloses a road accident rescue method and a road accident rescue system based on a C-V2X technology, wherein the road accident rescue system based on the C-V2X technology comprises a collision detection module, a rescue request module, a fault detection module, a C-V2X control module, a public-to-public distress module, a private-to-public distress module, a map updating module, a positioning module, an image acquisition module, an image analysis module, a signal receiving module, a path planning module, an alternating current module and a communication module; the C-V2X technology-based road accident rescue method comprises the steps of obtaining vehicle information and sending out a distress signal; accurately determining the position of the vehicle by updating the map; obtaining the road congestion degree of the road where the accident vehicle is located; and planning a rescue path. The method is used for road accident rescue based on the C-V2X technology, has the advantages of high accuracy and high efficiency, and can realize timely and effective rescue of accident vehicles or fault vehicles.)
1. A road accident rescue method based on a C-V2X technology is characterized by comprising the following steps:
the method comprises the following steps that firstly, whether a vehicle collides or not is detected through a sensor arranged inside a vehicle shell; if collision happens, directly turning to the step three;
step two, when vehicle collision is not detected, if other vehicle abnormalities or the body of a vehicle owner is uncomfortable are found, rescue is requested through a fault request program, and vehicle fault information is obtained through a vehicle fault detector;
step three, sending out distress signals to a road command center and a hospital emergency center through a public distress program; sending a distress signal to a private car owner through a private distress program;
step four, updating the city map through a map updating program; the accident vehicle position is determined through the locator, and the vehicle position is determined to be on the ground or an elevated road by combining with the updated map, so that the vehicle position is accurately determined;
performing the accident vehicle location determination includes the steps of:
firstly, detecting whether an automobile enters an elevated road from a ramp port;
secondly, when detecting that the automobile enters the elevated road from the ramp port, judging whether the received GPS signal is in an attenuation state continuously within a preset time;
if the GPS signal is continuously in an attenuation state within the preset time, determining that the automobile runs under the elevated road, namely on the ground;
fourthly, acquiring positioning information in the current state by the navigation device, wherein the positioning information is that the automobile is on a ground road under the elevated road;
acquiring an image of the position of the accident vehicle through an image acquisition program; analyzing the acquired image through an image analysis program to obtain the road congestion degree of the road where the accident vehicle is located;
step six, a road command center, a hospital emergency center or a private car owner receives the distress information of the fault car through a signal receiver, and calculates the distance between the signal receiving position and the signal sending position through a locator;
step seven, performing rescue path planning by combining the updated city map and the road congestion degree of the road where the fault vehicle is located through a path planning program;
and step eight, communicating with personnel in the accident vehicle through voice in the forward rescue process to obtain real-time information of the vehicle, judging casualty conditions, and soothing and nursing the casualty personnel.
2. A road accident rescue method based on C-V2X technology as claimed in claim 1, wherein in the fourth step, the updating the city map by the map updating program comprises:
(1) executing a map update process by multitask control in a navigation device configured by a vehicle;
(2) sequentially performing map update processing on a plurality of map files using map update data in a navigation device;
(3) and judging whether the map file required by the navigation processing is updated.
3. A road accident rescue method based on C-V2X technology as claimed in claim 2, wherein the step (3) of determining whether the map file required for the navigation process is completely updated comprises the steps of:
a step of acquiring a serial number management file in which a mark is written at a position corresponding to the serial number of all the map files after the update processing together with the map update processing file;
checking whether a mark is recorded in a position of the serial number management file corresponding to the serial number of the map file required for the navigation processing; if the mark is recorded, judging that the map file required by the navigation processing is updated, and if the mark is not recorded, judging that the map file required by the navigation processing is not updated;
the sequence number of the map file that has not been updated is not changed, and the sequence number in which the above-described flag is written is given to the map file that has been updated.
4. A road accident rescue method based on the C-V2X technology as claimed in claim 1, wherein in the fifth step, analyzing the collected image specifically includes:
1) extracting original data of traffic flow parameters from the image and preprocessing the data;
2) extracting an accidental congestion event, namely information at the position of a fault vehicle;
3) constructing sample data of the duration time of the accidental congestion event;
4) constructing a risk model of the sporadic congestion duration time, and estimating model parameters based on historical data;
5) and acquiring a real-time image, and estimating the duration of the occasional congestion.
5. A road accident rescue method based on the C-V2X technology as claimed in claim 4, wherein in the step 1), the extracting of the traffic flow parameter raw data from the image and the preprocessing are specifically:
acquiring traffic flow parameters of each section of the road through the image, wherein the traffic flow parameters specifically comprise the section, date, time, lane number, flow, speed and occupancy; processing missing values and abnormal values in the data;
the processing of the missing values includes: the missing value is represented as a missing attribute value, one is that the section is missing, and the records of some sections are null values; secondly, key parameters are lost, and when a certain parameter value in the original data is all 0 or is a certain fixed value, an error occurs when the data is recorded; deleting the data file lacking the attribute value aiming at the condition of the missing value, and ensuring the integrity of the attribute;
the processing of outliers includes: the vehicle speed is considered to be an abnormal value when the vehicle speed is more than 200km/h, and the processing mode is to replace the average value of the vehicle speed in the front time interval and the rear time interval which are connected with the vehicle speed; rejecting data with negative flow and occupancy;
in the step 2), extracting the sporadic congestion event includes:
calculating speed critical values corresponding to three inflection points of the road congestion degree according to the relation between the speed and the saturation degree, and judging whether a congestion event occurs or not based on the speed critical values;
judging whether the congestion event is sporadic congestion or not; if the road traffic flow parameters suddenly change at the congestion starting moment, the congestion event is an accidental congestion event, and otherwise, the congestion event is a frequent congestion event.
6. The C-V2X-based road accident rescue method according to claim 4, wherein in the step 3), constructing sample data of the duration of the sporadic congestion event comprises:
on the basis of the step 2), taking each sporadic congestion event as an observation sample based on historical data, and counting section numbers, dates, starting times, ending times and congestion duration of each sporadic congestion event, wherein the congestion duration is the difference between the ending time and the starting time of the congestion event;
acquiring traffic attributes and time attributes in an initial time period when an accidental congestion event occurs through a traffic detection system, and acquiring space attributes and road environment attributes of corresponding road sections by applying a GIS map matching technology;
each accidental congestion event is an observation sample, the starting time of each observation sample is used as a keyword, the section number, the date, the ending time and the congestion duration of the observation sample, the traffic attribute and the time attribute of the corresponding time period, and the space attribute and the road environment attribute of the corresponding road section are matched into the observation sample, and sample data of the accidental congestion event duration are constructed;
in the step 5), the estimating of the sporadic congestion duration specifically includes:
and acquiring real-time accidental congestion events and traffic attributes, space-time attributes and road environment attributes thereof as input variable data of the model, and estimating or predicting the duration of the current accidental congestion events.
7. A C-V2X technology-based road accident rescue system for the C-V2X technology-based road accident rescue method according to any one of claims 1-6, characterized in that the C-V2X technology-based road accident rescue system comprises:
the collision detection module is connected with the C-V2X control module and is used for detecting whether the vehicle collides or not through a sensor arranged inside a vehicle shell;
the rescue request module is connected with the C-V2X control module and is used for requesting rescue through a fault request program when vehicle collision is not detected;
the fault detection module is connected with the C-V2X control module and is used for acquiring vehicle fault information through the automobile fault detector;
the C-V2X control module is connected with the collision detection module, the rescue request module, the fault detection module, the public help seeking module, the private help seeking module, the map updating module, the positioning module, the image acquisition module, the image analysis module, the signal receiving module, the path planning module, the communication module and is used for controlling the normal operation of each module through the C-V2X technology;
the public help-seeking module is connected with the C-V2X control module and is used for sending help-seeking signals to a road command center and a hospital emergency center through a public help-seeking program;
the private help-seeking module is connected with the C-V2X control module and is used for sending a help-seeking signal to a private car owner through a private help-seeking program;
the map updating module is connected with the C-V2X control module and is used for updating the city map through a map updating program;
the positioning module is connected with the C-V2X control module and is used for determining the position of the accident vehicle through the positioner and determining the position of the vehicle on the ground or an elevated road by combining with the updated map;
the image acquisition module is connected with the C-V2X control module and is used for acquiring images of the positions of the accident vehicles through an image acquisition program;
the image analysis module is connected with the C-V2X control module and is used for analyzing the collected images through an image analysis program to obtain the road congestion degree of the road where the accident vehicle is located;
the signal receiving module is connected with the C-V2X control module and used for receiving the distress information of the fault vehicle through the signal receiver and calculating the distance between the signal receiving position and the signal sending position through the positioner;
the route planning module is connected with the C-V2X control module and is used for planning a rescue route by combining the updated city map and the road congestion degree of the road where the fault vehicle is located through a route planning program;
the communication module is connected with the C-V2X control module and is used for communicating with personnel in the accident vehicle through voice, judging the casualty condition and soothing and nursing the casualty personnel;
and the communication module is connected with the C-V2X control module and is used for realizing communication through the 5G NR.
8. A road accident rescue system based on C-V2X technology as claimed in claim 7, wherein the rescue request module comprises:
the request triggering unit is used for triggering rescue request sending operation through a request rescue key;
the information acquisition unit is used for acquiring the environmental information around the current vehicle and acquiring the geographical position information of the current vehicle when the rescue request sending instruction is detected;
the user information pre-storing unit is used for pre-packaging and storing user information in the help-seeking information and sending the user information to the receiving terminal through the rescue information, wherein the user information comprises one or more of the following information: name, age, height, weight, blood pressure, past medical history, and contact details of the emergency contact.
9. A road accident rescue system based on C-V2X technology as claimed in claim 7, wherein the help-for-public module comprises:
the system comprises a nearby searching unit, a road command center or a hospital emergency center, wherein the nearby searching unit is used for searching the nearest road command center or hospital emergency center in a map database according to the position information of the vehicle;
the information acquisition unit is used for acquiring the contact way of the retrieved road command center or hospital emergency center;
and the request sending unit is used for sending the help-seeking information to a rescue information receiving platform of a road command center or a hospital emergency center.
10. A road accident rescue system based on C-V2X technology as claimed in claim 7, wherein the help-for-privacy module comprises:
the contact person presetting unit is used for pre-storing the contact information of the emergency contact person;
and the recourse information sending unit is used for sending preset recourse information and real-time position information to the emergency contact.
Technical Field
The invention belongs to the technical field of intelligent driving, and particularly relates to a road accident rescue method and system based on a C-V2X technology.
Background
At present: C-V2X is commonly referred to as Cellular-V2X for direct communication, or PC5 or Silelink. The C-V2X has the advantage of being based on technology for high-speed mobile applications and further improved for car use cases, based on 802.11p research over many years, the fundamental development of wireless communication is observed and a new series of car applications needs to be enhanced to support safe and autonomous driving. C-V2X includes direct communication and network-based communication, and is intended to provide an evolved path for 5G and is forward/backward compatible. C-V2X based on 5G NR is intended to provide high productivity, support wide band, ultra-low latency and reliability for autonomous vehicle use cases, such as sensor sharing, intent sharing and 3D HD map updates. Since C-V2X direct communication is independent of cellular networks, it can operate without or with reliance on wireless network coverage. The C-V2X technology platform is security aware, robust and reliable, and can provide a rich, differentiated experience. However, C-V2X is not fully applied at present, and the advantages of high efficiency and sharing cannot be exerted particularly in road accident rescue.
Through the above analysis, the problems and defects of the prior art are as follows: at present, C-V2X is not fully applied, and the advantages of high efficiency and sharing cannot be exerted particularly in road accident rescue.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a road accident rescue method and system based on a C-V2X technology.
The invention is realized in such a way that a road accident rescue system based on C-V2X technology comprises:
the system comprises a collision detection module, a rescue request module, a fault detection module, a C-V2X control module, a public help seeking module, a private help seeking module, a map updating module, a positioning module, an image acquisition module, an image analysis module, a signal receiving module, a path planning module, an alternating current module and a communication module;
the collision detection module is connected with the C-V2X control module and is used for detecting whether the vehicle collides or not through a sensor arranged inside a vehicle shell;
the rescue request module is connected with the C-V2X control module and is used for requesting rescue through a fault request program when vehicle collision is not detected;
the fault detection module is connected with the C-V2X control module and is used for acquiring vehicle fault information through the automobile fault detector;
the C-V2X control module is connected with the collision detection module, the rescue request module, the fault detection module, the public help seeking module, the private help seeking module, the map updating module, the positioning module, the image acquisition module, the image analysis module, the signal receiving module, the path planning module, the communication module and is used for controlling the normal operation of each module through the C-V2X technology;
the public help-seeking module is connected with the C-V2X control module and is used for sending help-seeking signals to a road command center and a hospital emergency center through a public help-seeking program;
the private help-seeking module is connected with the C-V2X control module and is used for sending a help-seeking signal to a private car owner through a private help-seeking program;
the map updating module is connected with the C-V2X control module and is used for updating the city map through a map updating program;
the positioning module is connected with the C-V2X control module and is used for determining the position of the accident vehicle through the positioner and determining the position of the vehicle on the ground or an elevated road by combining with the updated map;
the image acquisition module is connected with the C-V2X control module and is used for acquiring images of the positions of the accident vehicles through an image acquisition program;
the image analysis module is connected with the C-V2X control module and is used for analyzing the collected images through an image analysis program to obtain the road congestion degree of the road where the accident vehicle is located;
the signal receiving module is connected with the C-V2X control module and used for receiving the distress information of the fault vehicle through the signal receiver and calculating the distance between the signal receiving position and the signal sending position through the positioner;
the route planning module is connected with the C-V2X control module and is used for planning a rescue route by combining the updated city map and the road congestion degree of the road where the fault vehicle is located through a route planning program;
the communication module is connected with the C-V2X control module and is used for communicating with personnel in the accident vehicle through voice, judging the casualty condition and soothing and nursing the casualty personnel;
and the communication module is connected with the C-V2X control module and is used for realizing communication through the 5G NR.
Further, the rescue request module includes:
the request triggering unit is used for triggering rescue request sending operation through a request rescue key;
the information acquisition unit is used for acquiring the environmental information around the current vehicle and acquiring the geographical position information of the current vehicle when the rescue request sending instruction is detected;
the user information pre-storing unit is used for pre-packaging and storing user information in the help-seeking information and sending the user information to the receiving terminal through the rescue information, wherein the user information comprises one or more of the following information: name, age, height, weight, blood pressure, past medical history, and contact details of the emergency contact.
Further, the public distress module comprises:
the system comprises a nearby searching unit, a road command center or a hospital emergency center, wherein the nearby searching unit is used for searching the nearest road command center or hospital emergency center in a map database according to the position information of the vehicle;
the information acquisition unit is used for acquiring the contact way of the retrieved road command center or hospital emergency center;
and the request sending unit is used for sending the help-seeking information to a rescue information receiving platform of a road command center or a hospital emergency center.
Further, the help-to-private module comprises:
the contact person presetting unit is used for pre-storing the contact information of the emergency contact person;
and the recourse information sending unit is used for sending preset recourse information and real-time position information to the emergency contact.
The invention also aims to provide a road accident rescue method based on the C-V2X technology, which comprises the following steps:
the method comprises the following steps that firstly, whether a vehicle collides or not is detected through a sensor arranged inside a vehicle shell; if collision happens, directly turning to the step three;
step two, when vehicle collision is not detected, if other vehicle abnormalities or the body of a vehicle owner is uncomfortable are found, rescue is requested through a fault request program, and vehicle fault information is obtained through a vehicle fault detector;
step three, sending out distress signals to a road command center and a hospital emergency center through a public distress program; sending a distress signal to a private car owner through a private distress program;
step four, updating the city map through a map updating program; the accident vehicle position is determined through the locator, and the vehicle position is determined to be on the ground or an elevated road by combining with the updated map, so that the vehicle position is accurately determined;
acquiring an image of the position of the accident vehicle through an image acquisition program; analyzing the acquired image through an image analysis program to obtain the road congestion degree of the road where the accident vehicle is located;
step six, a road command center, a hospital emergency center or a private car owner receives the distress information of the fault car through a signal receiver, and calculates the distance between the signal receiving position and the signal sending position through a locator;
step seven, performing rescue path planning by combining the updated city map and the road congestion degree of the road where the fault vehicle is located through a path planning program;
and step eight, communicating with personnel in the accident vehicle through voice in the forward rescue process to obtain real-time information of the vehicle, judging casualty conditions, and soothing and nursing the casualty personnel.
Further, in the fourth step, the updating the city map by the map updating program includes:
(1) executing a map update process by multitask control in a navigation device configured by a vehicle;
(2) sequentially performing map update processing on a plurality of map files using map update data in a navigation device;
(3) and judging whether the map file required by the navigation processing is updated.
Further, the step (3) of determining whether the map file required for the navigation processing is completely updated includes the following steps:
a step of acquiring a serial number management file in which a mark is written at a position corresponding to the serial number of all the map files after the update processing together with the map update processing file;
checking whether a mark is recorded in a position of the serial number management file corresponding to the serial number of the map file required for the navigation processing; if the mark is recorded, judging that the map file required by the navigation processing is updated, and if the mark is not recorded, judging that the map file required by the navigation processing is not updated;
the sequence number of the map file that has not been updated is not changed, and the sequence number in which the above-described flag is written is given to the map file that has been updated.
Further, in the fourth step, the determining the position of the accident vehicle comprises the following steps:
firstly, detecting whether an automobile enters an elevated road from a ramp port;
secondly, when detecting that the automobile enters the elevated road from the ramp port, judging whether the received GPS signal is in an attenuation state continuously within a preset time;
if the GPS signal is continuously in an attenuation state within the preset time, determining that the automobile runs under the elevated road, namely on the ground;
and fourthly, acquiring the positioning information in the current state by the navigation device, wherein the positioning information is that the automobile is on the ground road under the elevated road.
Further, in the fifth step, analyzing the collected image specifically includes:
1) extracting original data of traffic flow parameters from the image and preprocessing the data;
2) extracting an accidental congestion event, namely information at the position of a fault vehicle;
3) constructing sample data of the duration time of the accidental congestion event;
4) constructing a risk model of the sporadic congestion duration time, and estimating model parameters based on historical data;
5) and acquiring a real-time image, and estimating the duration of the occasional congestion.
Further, in the step 1), extracting the traffic flow parameter raw data from the image and preprocessing the traffic flow parameter raw data specifically include:
acquiring traffic flow parameters of each section of the road through the image, wherein the traffic flow parameters specifically comprise the section, date, time, lane number, flow, speed and occupancy; processing missing values and abnormal values in the data;
the processing of the missing values includes: the missing value is represented as a missing attribute value, one is that the section is missing, and the records of some sections are null values; secondly, key parameters are lost, and when a certain parameter value in the original data is all 0 or is a certain fixed value, an error occurs when the data is recorded; deleting the data file lacking the attribute value aiming at the condition of the missing value, and ensuring the integrity of the attribute;
the processing of outliers includes: the vehicle speed is considered to be an abnormal value when the vehicle speed is more than 200km/h, and the processing mode is to replace the average value of the vehicle speed in the front time interval and the rear time interval which are connected with the vehicle speed; and rejecting data with negative flow and occupancy.
Further, in the step 2), the extracting of the sporadic congestion event includes:
calculating speed critical values corresponding to three inflection points of the road congestion degree according to the relation between the speed and the saturation degree, and judging whether a congestion event occurs or not based on the speed critical values;
judging whether the congestion event is sporadic congestion or not; if the road traffic flow parameters suddenly change at the congestion starting moment, the congestion event is an accidental congestion event, and otherwise, the congestion event is a frequent congestion event.
Further, in the step 3), constructing sample data of the duration of the sporadic congestion event includes:
on the basis of the step 2), taking each sporadic congestion event as an observation sample based on historical data, and counting section numbers, dates, starting times, ending times and congestion duration of each sporadic congestion event, wherein the congestion duration is the difference between the ending time and the starting time of the congestion event;
acquiring traffic attributes and time attributes in an initial time period when an accidental congestion event occurs through a traffic detection system, and acquiring space attributes and road environment attributes of corresponding road sections by applying a GIS map matching technology;
each accidental congestion event is an observation sample, the starting time of each observation sample is used as a keyword, the section number, the date, the ending time and the congestion duration of each observation sample, the traffic attribute and the time attribute of the corresponding time period, and the space attribute and the road environment attribute of the corresponding road section are matched into the observation samples, and sample data of the accidental congestion event duration are constructed.
Further, in the step 5), estimating the sporadic congestion duration specifically includes:
and acquiring real-time accidental congestion events and traffic attributes, space-time attributes and road environment attributes thereof as input variable data of the model, and estimating or predicting the duration of the current accidental congestion events.
By combining all the technical schemes, the invention has the advantages and positive effects that: according to the invention, the optimization of the distress information is realized through collision detection and active distress, the distress failure caused by the discomfort of the owner body is avoided, the coverage range of road rescue is wider, and the practicability is better; the accurate judgment of the vehicle position can be realized through map updating, the accurate grasp of traffic information near the vehicle can be realized, and rescue planning is convenient to carry out; the rescue signal can be transmitted to a private car owner, the rescue range can be expanded, and the loss caused by incapability of timely rescue due to too long distance of a hospital or a traffic police is avoided. The method is used for road accident rescue based on the C-V2X technology, has the advantages of high accuracy and high efficiency, and can realize timely and effective rescue of accident vehicles or fault vehicles.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a block diagram of a road accident rescue system based on the C-V2X technology according to an embodiment of the present invention.
Fig. 2 is a flowchart of a road accident rescue method based on the C-V2X technology provided by the embodiment of the invention.
Fig. 3 is a flowchart of a city map update performed by a map update program according to an embodiment of the present invention.
Fig. 4 is a flow chart for performing an accident vehicle location determination provided by an embodiment of the present invention.
Fig. 5 is a flow chart of analyzing an acquired image according to an embodiment of the present invention.
In fig. 1: 1. a collision detection module; 2. a rescue request module; 3. a fault detection module; 4. a C-V2X control module; 5. a public help-seeking module; 6. a private help-seeking module; 7. a map update module; 8. a positioning module; 9. an image acquisition module; 10. an image analysis module; 11. a signal receiving module; 12. a path planning module; 13. an alternating current module; 14. and a communication module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a road accident rescue method and system based on a C-V2X technology, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the road accident rescue system based on the C-V2X technology provided by the embodiment of the present invention includes:
the system comprises a
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the public help-seeking
the private help-seeking
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The rescue request module in the embodiment of the invention comprises:
the request triggering unit is used for triggering rescue request sending operation through a request rescue key;
the information acquisition unit is used for acquiring the environmental information around the current vehicle and acquiring the geographical position information of the current vehicle when the rescue request sending instruction is detected;
the user information pre-storing unit is used for pre-packaging and storing user information in the help-seeking information and sending the user information to the receiving terminal through the rescue information, wherein the user information comprises one or more of the following information: name, age, height, weight, blood pressure, past medical history, and contact details of the emergency contact.
The public SOS module in the embodiment of the invention comprises:
the system comprises a nearby searching unit, a road command center or a hospital emergency center, wherein the nearby searching unit is used for searching the nearest road command center or hospital emergency center in a map database according to the position information of the vehicle;
the information acquisition unit is used for acquiring the contact way of the retrieved road command center or hospital emergency center;
and the request sending unit is used for sending the help-seeking information to a rescue information receiving platform of a road command center or a hospital emergency center.
The private help seeking module in the embodiment of the invention comprises:
the contact person presetting unit is used for pre-storing the contact information of the emergency contact person;
and the recourse information sending unit is used for sending preset recourse information and real-time position information to the emergency contact.
As shown in fig. 2, the road accident rescue method based on the C-V2X technology provided by the embodiment of the invention comprises the following steps:
s101, detecting whether a vehicle collides or not through a sensor arranged in a vehicle shell; if collision happens, directly turning to S103;
s102, when vehicle collision is not detected, if other vehicle abnormalities or discomfort of a vehicle owner is found, rescue is requested through a fault request program, and vehicle fault information is obtained through a vehicle fault detector;
s103, sending out distress signals to a road command center and a hospital emergency center through a public distress program; sending a distress signal to a private car owner through a private distress program;
s104, updating the city map through a map updating program; the accident vehicle position is determined through the locator, and the vehicle position is determined to be on the ground or an elevated road by combining with the updated map, so that the vehicle position is accurately determined;
s105, acquiring an image of the position of the accident vehicle through an image acquisition program; analyzing the acquired image through an image analysis program to obtain the road congestion degree of the road where the accident vehicle is located;
s106, a road command center, a hospital emergency center or a private car owner receives the distress information of the fault car through a signal receiver, and calculates the distance between the signal receiving position and the signal sending position through a locator;
s107, performing rescue path planning by combining the updated city map and the road congestion degree of the road where the fault vehicle is located through a path planning program;
and S108, communicating with personnel in the accident vehicle through voice in the forward rescue process to obtain real-time information of the vehicle, judging casualty conditions, and soothing and nursing the casualty personnel.
As shown in fig. 3, in step S104, the updating the city map by the map updating program according to the embodiment of the present invention includes:
s201, performing a map update process by multitask control in a navigation device disposed in a vehicle;
s202, using the map updating data to sequentially update a plurality of map files in the navigation device;
s203, judging whether the map file required by the navigation processing is updated.
In step S203, the step of determining whether the map file required for the navigation processing is updated includes the following steps:
a step of acquiring a serial number management file in which a mark is written at a position corresponding to the serial number of all the map files after the update processing together with the map update processing file;
checking whether a mark is recorded in a position of the serial number management file corresponding to the serial number of the map file required for the navigation processing; if the mark is recorded, judging that the map file required by the navigation processing is updated, and if the mark is not recorded, judging that the map file required by the navigation processing is not updated;
the sequence number of the map file that has not been updated is not changed, and the sequence number in which the above-described flag is written is given to the map file that has been updated.
As shown in fig. 4, in step S104, the determining the position of the accident vehicle according to the embodiment of the present invention includes the following steps:
s301, detecting whether an automobile enters the elevated road from a ramp port;
s302, when detecting that the automobile enters the elevated road from the ramp port, judging whether the received GPS signal is in an attenuation state continuously within preset time;
s303, if the GPS signal is continuously in an attenuation state within preset time, determining that the automobile runs under an elevated road, namely on the ground;
s304, the navigation device obtains the positioning information in the current state that the automobile is on the ground road under the elevated road.
As shown in fig. 5, in step S105, analyzing the acquired image specifically includes:
s401, extracting original data of traffic flow parameters from the image and preprocessing the data;
s402, extracting an accidental congestion event, namely information of the position of a fault vehicle;
s403, constructing sample data of the duration time of the sporadic congestion event;
s404, constructing a risk model of the sporadic congestion duration time, and estimating model parameters based on historical data;
and S405, acquiring a real-time image and estimating the duration of the occasional congestion.
In step S401, the extracting and preprocessing of the traffic flow parameter raw data from the image provided in the embodiment of the present invention specifically includes:
acquiring traffic flow parameters of each section of the road through the image, wherein the traffic flow parameters specifically comprise the section, date, time, lane number, flow, speed and occupancy; processing missing values and abnormal values in the data;
the processing of the missing values includes: the missing value is represented as a missing attribute value, one is that the section is missing, and the records of some sections are null values; secondly, key parameters are lost, and when a certain parameter value in the original data is all 0 or is a certain fixed value, an error occurs when the data is recorded; deleting the data file lacking the attribute value aiming at the condition of the missing value, and ensuring the integrity of the attribute;
the processing of outliers includes: the vehicle speed is considered to be an abnormal value when the vehicle speed is more than 200km/h, and the processing mode is to replace the average value of the vehicle speed in the front time interval and the rear time interval which are connected with the vehicle speed; and rejecting data with negative flow and occupancy.
In step S402, the extracting of the sporadic congestion event according to the embodiment of the present invention includes:
calculating speed critical values corresponding to three inflection points of the road congestion degree according to the relation between the speed and the saturation degree, and judging whether a congestion event occurs or not based on the speed critical values;
judging whether the congestion event is sporadic congestion or not; if the road traffic flow parameters suddenly change at the congestion starting moment, the congestion event is an accidental congestion event, and otherwise, the congestion event is a frequent congestion event.
In step S403, the sample data for constructing the duration of the sporadic congestion event provided in the embodiment of the present invention includes:
on the basis of the step S402, taking each sporadic congestion event as an observation sample based on the historical data, and counting a section number, a date, a start time, an end time, and a congestion duration of each sporadic congestion event, where the congestion duration is a difference between the end time and the start time of the congestion event;
acquiring traffic attributes and time attributes in an initial time period when an accidental congestion event occurs through a traffic detection system, and acquiring space attributes and road environment attributes of corresponding road sections by applying a GIS map matching technology;
each accidental congestion event is an observation sample, the starting time of each observation sample is used as a keyword, the section number, the date, the ending time and the congestion duration of each observation sample, the traffic attribute and the time attribute of the corresponding time period, and the space attribute and the road environment attribute of the corresponding road section are matched into the observation samples, and sample data of the accidental congestion event duration are constructed.
In step S405, the estimating of the sporadic congestion duration provided by the embodiment of the present invention specifically includes:
and acquiring real-time accidental congestion events and traffic attributes, space-time attributes and road environment attributes thereof as input variable data of the model, and estimating or predicting the duration of the current accidental congestion events.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed herein, which is within the spirit and principle of the present invention, should be covered by the present invention.